Scalable Packet Classification Using Interpreting—A Crossplatform Multi-core Solution

Packet classification is an enabling technology to support advanced Internet services. It is still a challenge for a software solution to achieve 10Gbps (line-rate) classification speed. This paper presents a classification algorithm that can be efficiently implemented on a multi-core architecture with or without cache. The algorithm embraces the holistic notion of exploiting application characteristics, considering the capabilities of the CPU and the memory hierarchy, and performing appropriate data partitioning. The classification algorithm adopts two stages: searching on a reduction tree and searching on a list of ranges. This decision is made based on a classification heuristic: the size of the range list is limited after the first stage search. Optimizations are then designed to speed up the two-stage execution. To exploit the speed gap (1) between the CPU an